Peter Aba has put together a a set of visualizations around the popularity of various PHP projects using the phpmetrics tool. He decided to run it against several projects he knows of and share the results.

I came across a new tool called phpmetrics. It can be used for, what a surprise, calculating and displaying metrics for php. I fell in love with this cute little tool in an instance and decided to run it on some php projects that I consider important. I'm aware of the fact that the list is currently far from complete, but it's probably still worth a look. I especially love the "maintenability" (sic!) reports, I find those big red spots just as disgusting as I find ugly code the same.

He's broken it up into a few different sections with lots of different projects under each:

Frameworks

CMS

E-commerce

Development tools

There's also an "Other" (and "Backfire") category that contains the results for the results of phpmetrics itself. He also includes a few issues he ran across during the processing of the metrics, some with the phpmetrics tool itself and some with the libraries themselves.

The web is a place where everyone is in your backyard. This can be both a blessing and a curse. How do you know where your website traffic is coming from and how much of it there is? [...] How was traffic led to your website in the first place and why? How long do people stick around and what do they like the most about your site? These are all some of the many questions you can answer with web analytic software, but the real question is why would you want to answer these questions at all and what's the best way to look at the answer?

[...] If we look at a heat map it's easier to spot where the majority of our visitors and traffic are coming from, geographically. It also helps us understand that people visiting a virtual space can, and will, be physically located in different parts of the world.

He includes the steps to recreate a map like the one included in this page showing the current view statistics on his site. He uses a MySQL backend to store the GeoIP data and parses out the Apache "access_log" to get the IPs of the visiting users. He then runs these against the GeoIP data and passes this country data on to Google's visualization for handling. He also recommends using the tools offered by the Google Webmaster Tools to further enhance your introspection into your site's visitors.